As UX Designer for iptiQ by SwissRe in the insurtech industry, my role involved the research and the design of a new product of HEMSÄKER, the household insurance branded IKEA and SwissRe.
- User research.
- Analysis and Synthesis of the data collected from researches.
- Reports of findings and insights to be shared and discussed with stakeholders.
- Competitive analysis.
- Ideation of the new product’s features.
- UI design from low fidelity until the interactive prototype.
- Data driven decisions gathering data from Mouse-flow (heat-maps, scrolls and clicks) and Tableau (conversion rates).
- Provided scenarios and designs for A/B test.
- Alignments with developers, documentation, and handover.
- Alignments with all the stakeholders (marketing, business, product, data scientists, content writers, developers, designers).
- Usability tests and design iterations.
- Findings and Insights reports.
- Update of Design Library and Design System Manager.
The product I am responsible of is not yet implemented in the IKEA HEMSÄKER’s website. Moreover, is protected by NDA, therefore the screen I share as featured image is of a project phase already online and public, and does not represent the product I am working on. As soon as the product I worked on will be available online, I can share the designs here.
The user research involved:
User interviews for 36 participants divided in 3 groups to collect qualitative insights about needs, frustrations, past and current experiences, opportunities, happy paths and so on.
Participants were recruited through a platform. The target was given by the Persona that were individuated for HEMSÄKER.
To synthesise those insights I arranged three affinity maps (one fo each group) to group the quotes of participants according both the affinities and to our research questions.
Then I replicated the same process to have a look also at the insights for the total of participants.
Surveys to collect quantitative data
The pool of the survey was 300 participants. the research goals were similar to the ones for the user interviews, to validate and quantify in percentage the answers to our questions.
The results were arranged in a report first, then shared and discussed with stakeholders.
There was no need to identify a specific Personas for this product because were identified already for HEMSÄKER. I used these Personas in combination with data from the user research and arranged them in an Impact map.
Impact Mapping is a graphic strategy planning method to decide which features to build into a product. In order to do that, I combined research goals, Persona, results from the user interviews (qualitative data), features that can achieve the goal to finally create user stories.
- Why The business goal answers the most important question: Why do we want to do something?
- Who are the actors / personas which have an impact on the outcome?
- How does the business goal have (positive / negative) impact on the behaviour of the actors?
- What are the deliverables to spark impact and to achieve the goal: Epics, Features, User Stories
- User Story to bring into the backlog
Thanks to all these data and the Impact mapping process, I could define the features needed for the MVP of the product.
The whole experience would have to include:
- Marketing campaigns to inform the users (newsletters, social media ads, In store ads)
- Presence of the new product in the early stage of the user journey (Landing Page), without obstructing the main purpose of the user
- Presence of the new product during the journey, only on touch points where it will not distract the user from its main goal.
- Presence of the new product in the Customer Self Service (CSS).
- Reachable information about the new product from the top navigation, which will disappear once the user is deep in the journey.
User flow for the user lands on HEMSÄKER Landing page, interacts with the new product opening different scenario to finally reach its goal. Includes the Customer Self Service portal.
Alignment with devs
During the entire process I always kept the dialogue open with developers for insights about technical feasibility and estimation of effort, in order to be all aligned on which feature could come in.
I collaborated with the Business stakeholder for what concern a user experience prioritisation of features for the product I was working on. Needless to say, for big projects the prioritisation depends from different factors, involves different departments and was at the end done between the Heads and Product Owners.
Placement of the new feature in the landing page and along the journey
To define the positioning of the new product, both in the Landing Page and during the whole journey, I gathered data in Mouse- flow and Tableau.
Using mouse flow I was able to look at scrolls, visibility, clicks rate and movements of the users using our website. I also watched recordings, focusing on the ones marked with high frictions.
I collected data for two different timeframes, taking care of the release date of specific features. I arranged the findings in two tables and documented in Confluence, reporting proposed solution for the placement of the new feature.
Using Tableau I could check the conversion rate of existing features from the Landing page to the other pages of the website.
Low fidelity wireframes
using Sketch, I designed low fidelity wireframes to start the structure of the first version of the user interface. (These two are only a part).
Once I was sure that I covered all the scenarios, and aligned with devs, I transformed the low fidelity wireframes in middle fidelity, adding the styles from our Brand library. I uploaded the art-boards from Sketch to InVision in order to create an interactive prototype to use for the upcoming usability tests. In this phase the designs were in middle fidelity.
I recruited 6 participants and run moderated usability test for the whole journey, included the Customer Self Service portal.
I assembled a form for each participants to take notes, and then assembled an overall report of findings with notes, comments on pain point and happy points, observations, and proposed solution for iteration.
Iteration in high fidelity
Basing on the findings and comments I documented earlier, I iterated in High Fidelity.
During my assignment by SwissRe I was responsible also for the re-design of existing components for our Design Library: